Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/12005
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dc.contributor.authorDemir, Ozlem Tugfe-
dc.contributor.authorBjornson, Emil-
dc.contributor.authorSanguinetti, Luca-
dc.date.accessioned2025-01-10T21:00:47Z-
dc.date.available2025-01-10T21:00:47Z-
dc.date.issued2025-
dc.identifier.issn1536-1276-
dc.identifier.issn1558-2248-
dc.identifier.urihttps://doi.org/10.1109/TWC.2024.3495226-
dc.descriptionBjornson, Emil/0000-0002-5954-434X; Sanguinetti, Luca/0000-0002-2577-4091en_US
dc.description.abstractAccurate estimation of the cascaded channel from a user equipment (UE) to a base station (BS) via each reconfigurable intelligent surface (RIS) element is critical to realizing the full potential of the RIS's ability to control the overall channel. The number of parameters to be estimated is equal to the number of RIS elements, requiring an equal number of pilots unless an underlying structure can be identified. In this paper, we show how the spatial correlation inherent in the different RIS channels provides this desired structure. We first optimize the RIS phase-shift pattern using a much-reduced pilot length (determined by the rank of the spatial correlation matrices) to minimize the mean square error (MSE) in the channel estimation under electromagnetic interference. In addition to considering the linear minimum MSE (LMMSE) channel estimator, we propose a novel channel estimator that requires only knowledge of the array geometry while not requiring any user-specific statistical information. We call this the reduced-subspace least squares (RS-LS) estimator and optimize the RIS phase-shift pattern for it. This novel estimator significantly outperforms the conventional LS estimator. For both the LMMSE and RS-LS estimators, the proposed optimized RIS configurations result in significant channel estimation improvements over the benchmarks.en_US
dc.description.sponsorshipSwedish Foundation for Strategic Research [FFL18-0277]; Italian Ministry of Education and Research (MUR); Garden Project (PRIN 2022 Program)en_US
dc.description.sponsorshipThis work was supported by Swedish Foundation for Strategic Research under Grant FFL18-0277. The work of Luca Sanguinetti was supported by Italian Ministry of Education and Research (MUR) in the Framework of the FoReLab Project (Departments of Excellence) and the Garden Project (PRIN 2022 Program). An earlier version of this paper was presented at the IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM) [DOI: 10.1109/SAM53842.2022.9827790].en_US
dc.language.isoenen_US
dc.publisherIEEE-Inst Electrical Electronics Engineers incen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectChannel Estimationen_US
dc.subjectElectromagnetic Interferenceen_US
dc.subjectReconfigurable Intelligent Surfacesen_US
dc.subjectCorrelationen_US
dc.subjectGeometryen_US
dc.subjectScatteringen_US
dc.subjectWireless Communicationen_US
dc.subjectCoherenceen_US
dc.subjectTrainingen_US
dc.subjectTerahertz Communicationsen_US
dc.subjectRisen_US
dc.subjectChannel Estimationen_US
dc.subjectReduced-Subspace Least Squaresen_US
dc.subjectSpatial Correlation Matrixen_US
dc.subjectPilot Designen_US
dc.subjectElectromagnetic Interferenceen_US
dc.titleEfficient Channel Estimation With Shorter Pilots in Ris-Aided Communications: Using Array Geometries and Interference Statisticsen_US
dc.typeArticleen_US
dc.departmentTOBB University of Economics and Technologyen_US
dc.identifier.volume24en_US
dc.identifier.issue1en_US
dc.identifier.startpage462en_US
dc.identifier.endpage478en_US
dc.authoridBjornson, Emil/0000-0002-5954-434X-
dc.authoridSanguinetti, Luca/0000-0002-2577-4091-
dc.identifier.wosWOS:001395655800012-
dc.identifier.scopus2-s2.0-85210273077-
dc.identifier.doi10.1109/TWC.2024.3495226-
dc.authorwosidBjörnson, Emil/AAD-4840-2019-
dc.authorwosidSanguinetti, Luca/B-5063-2018-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
dc.identifier.wosqualityQ1-
dc.description.woscitationindexScience Citation Index Expanded-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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